def create_and_check_xxx_model(self, config, input_ids, token_type_ids,
input_mask, sequence_labels,
token_labels, choice_labels):
model = TFXxxModel(config=config)
inputs = {
'input_ids': input_ids,
'attention_mask': input_mask,
'token_type_ids': token_type_ids
}
sequence_output, pooled_output = model(inputs)
inputs = [input_ids, input_mask]
sequence_output, pooled_output = model(inputs)
sequence_output, pooled_output = model(input_ids)
result = {
"sequence_output": sequence_output.numpy(),
"pooled_output": pooled_output.numpy(),
}
self.parent.assertListEqual(
list(result["sequence_output"].shape),
[self.batch_size, self.seq_length, self.hidden_size])
self.parent.assertListEqual(list(result["pooled_output"].shape),
[self.batch_size, self.hidden_size])
def create_and_check_xxx_model(self, config, input_ids, token_type_ids,
input_mask, sequence_labels,
token_labels, choice_labels):
model = TFXxxModel(config=config)
inputs = {
"input_ids": input_ids,
"attention_mask": input_mask,
"token_type_ids": token_type_ids
}
result = model(inputs)
inputs = [input_ids, input_mask]
result = model(inputs)
result = model(input_ids)
self.parent.assertListEqual(
list(result["last_hidden_state"].shape),
[self.batch_size, self.seq_length, self.hidden_size])
self.parent.assertListEqual(list(result["pooler_output"].shape),
[self.batch_size, self.hidden_size])
def test_model_from_pretrained(self):
for model_name in ['xxx-base-uncased']:
model = TFXxxModel.from_pretrained(model_name, cache_dir=CACHE_DIR)
self.assertIsNotNone(model)
def test_model_from_pretrained(self):
cache_dir = "/tmp/transformers_test/"
for model_name in ['xxx-base-uncased']:
model = TFXxxModel.from_pretrained(model_name, cache_dir=cache_dir)
shutil.rmtree(cache_dir)
self.assertIsNotNone(model)